{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_csv('train.csv')\n",
    "# df = df.sample(frac=0.2, random_state=99)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9917530, 54)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is a large data set with near 10 million observations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x27b0a9f1a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "n, bins, patches = plt.hist(df.prop_country_id, 100, density = 1, facecolor='blue', alpha=0.75)\n",
    "plt.xlabel('Property country Id')\n",
    "plt.title('Histogram of prop_country_id')\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "prop_country_id\n",
       "219    6052976\n",
       "100     622810\n",
       "55      376219\n",
       "31      309434\n",
       "99      268393\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('prop_country_id').size().nlargest(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2657d2de630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n, bins, patches = plt.hist(df.visitor_location_country_id, 100, density = 1, facecolor='blue', alpha=0.75)\n",
    "plt.xlabel('Visitor location country Id')\n",
    "plt.title('Histogram of visitor_location_country_id')\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "visitor_location_country_id\n",
       "219    5778805\n",
       "100     990487\n",
       "55      580072\n",
       "216     434568\n",
       "220     350433\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('visitor_location_country_id').size().nlargest(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data is anonymized, so determining the exact country or city to which a consumer plans to travel to is not possible. However, it is evident that the largest country (labeled 219) is the United States. The largest country has 61% of all observations. Out of those, 58% of searches are made by consumers also located in this country, suggesting that the country has a large territory with a large fraction of domestic travel. The price currency also suggested that the largest country being the United States.\n",
    "\n",
    "Therefore, to improve the computational efficiency, we are going to predict Click-Through for US visitors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['srch_id', 'date_time', 'site_id', 'visitor_location_country_id',\n",
       "       'visitor_hist_starrating', 'visitor_hist_adr_usd', 'prop_country_id',\n",
       "       'prop_id', 'prop_starrating', 'prop_review_score', 'prop_brand_bool',\n",
       "       'prop_location_score1', 'prop_location_score2',\n",
       "       'prop_log_historical_price', 'position', 'price_usd', 'promotion_flag',\n",
       "       'srch_destination_id', 'srch_length_of_stay', 'srch_booking_window',\n",
       "       'srch_adults_count', 'srch_children_count', 'srch_room_count',\n",
       "       'srch_saturday_night_bool', 'srch_query_affinity_score',\n",
       "       'orig_destination_distance', 'random_bool', 'comp1_rate', 'comp1_inv',\n",
       "       'comp1_rate_percent_diff', 'comp2_rate', 'comp2_inv',\n",
       "       'comp2_rate_percent_diff', 'comp3_rate', 'comp3_inv',\n",
       "       'comp3_rate_percent_diff', 'comp4_rate', 'comp4_inv',\n",
       "       'comp4_rate_percent_diff', 'comp5_rate', 'comp5_inv',\n",
       "       'comp5_rate_percent_diff', 'comp6_rate', 'comp6_inv',\n",
       "       'comp6_rate_percent_diff', 'comp7_rate', 'comp7_inv',\n",
       "       'comp7_rate_percent_diff', 'comp8_rate', 'comp8_inv',\n",
       "       'comp8_rate_percent_diff', 'click_bool', 'gross_bookings_usd',\n",
       "       'booking_bool'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "us = df.loc[df['visitor_location_country_id'] == 219]\n",
    "us = us.sample(frac=0.6, random_state=99)\n",
    "del us['visitor_location_country_id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3467283, 53)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "srch_id                            0\n",
       "date_time                          0\n",
       "site_id                            0\n",
       "visitor_hist_starrating      3326522\n",
       "visitor_hist_adr_usd         3325727\n",
       "prop_country_id                    0\n",
       "prop_id                            0\n",
       "prop_starrating                    0\n",
       "prop_review_score               3297\n",
       "prop_brand_bool                    0\n",
       "prop_location_score1               0\n",
       "prop_location_score2          804564\n",
       "prop_log_historical_price          0\n",
       "position                           0\n",
       "price_usd                          0\n",
       "promotion_flag                     0\n",
       "srch_destination_id                0\n",
       "srch_length_of_stay                0\n",
       "srch_booking_window                0\n",
       "srch_adults_count                  0\n",
       "srch_children_count                0\n",
       "srch_room_count                    0\n",
       "srch_saturday_night_bool           0\n",
       "srch_query_affinity_score    3174829\n",
       "orig_destination_distance     431936\n",
       "random_bool                        0\n",
       "comp1_rate                   3425367\n",
       "comp1_inv                    3422653\n",
       "comp1_rate_percent_diff      3432567\n",
       "comp2_rate                   1732043\n",
       "comp2_inv                    1646681\n",
       "comp2_rate_percent_diff      3025276\n",
       "comp3_rate                   2050871\n",
       "comp3_inv                    1961789\n",
       "comp3_rate_percent_diff      3050381\n",
       "comp4_rate                   3375167\n",
       "comp4_inv                    3358039\n",
       "comp4_rate_percent_diff      3426746\n",
       "comp5_rate                   2010083\n",
       "comp5_inv                    1920614\n",
       "comp5_rate_percent_diff      2891977\n",
       "comp6_rate                   3419720\n",
       "comp6_inv                    3415605\n",
       "comp6_rate_percent_diff      3448025\n",
       "comp7_rate                   3406120\n",
       "comp7_inv                    3398025\n",
       "comp7_rate_percent_diff      3440150\n",
       "comp8_rate                   1651208\n",
       "comp8_inv                    1589457\n",
       "comp8_rate_percent_diff      2897215\n",
       "click_bool                         0\n",
       "gross_bookings_usd           3369149\n",
       "booking_bool                       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, we have a lot of missing data in many features. We are going to drop features that have more than 90% of NaN, plus date_time, srch_id, prop_id, and impute the three features, they are prop_review_score, prop_location_score2, orig_destination_distance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols_to_drop = ['date_time', 'visitor_hist_starrating', 'visitor_hist_adr_usd', 'srch_query_affinity_score', 'comp1_rate', 'comp1_inv', 'comp1_rate_percent_diff', 'comp2_rate_percent_diff', 'comp3_rate_percent_diff', 'comp4_rate_percent_diff', 'comp5_rate_percent_diff', 'comp6_rate_percent_diff', 'comp7_rate_percent_diff', 'comp8_rate_percent_diff', 'comp2_rate', 'comp3_rate', 'comp4_rate', 'comp5_rate', 'comp6_rate', 'comp7_rate', 'comp8_rate', 'comp2_inv', 'comp3_inv', 'comp4_inv', 'comp5_inv', 'comp6_inv', 'comp7_inv', 'comp8_inv', 'gross_bookings_usd', 'srch_id', 'prop_id']\n",
    "us.drop(cols_to_drop, axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "site_id                           0\n",
       "prop_country_id                   0\n",
       "prop_starrating                   0\n",
       "prop_review_score              3297\n",
       "prop_brand_bool                   0\n",
       "prop_location_score1              0\n",
       "prop_location_score2         804564\n",
       "prop_log_historical_price         0\n",
       "position                          0\n",
       "price_usd                         0\n",
       "promotion_flag                    0\n",
       "srch_destination_id               0\n",
       "srch_length_of_stay               0\n",
       "srch_booking_window               0\n",
       "srch_adults_count                 0\n",
       "srch_children_count               0\n",
       "srch_room_count                   0\n",
       "srch_saturday_night_bool          0\n",
       "orig_destination_distance    431936\n",
       "random_bool                       0\n",
       "click_bool                        0\n",
       "booking_bool                      0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### prop_review_score, Random imputation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "def randomiseMissingData(df2):\n",
    "    \"randomise missing data for DataFrame (within a column)\"\n",
    "    df = df2.copy()\n",
    "    for col in df.columns:\n",
    "        data = df['prop_review_score']\n",
    "        mask = data.isnull()\n",
    "        samples = random.choices( data[~mask].values , k = mask.sum() )\n",
    "        data[mask] = samples\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SusanLi\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\ipykernel_launcher.py:9: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  if __name__ == '__main__':\n"
     ]
    }
   ],
   "source": [
    "us = randomiseMissingData(us)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.8523584605006285"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us['prop_review_score'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def randomiseMissingData(df2):\n",
    "    \"randomise missing data for DataFrame (within a column)\"\n",
    "    df = df2.copy()\n",
    "    for col in df.columns:\n",
    "        data = df['prop_location_score2']\n",
    "        mask = data.isnull()\n",
    "        samples = random.choices( data[~mask].values , k = mask.sum() )\n",
    "        data[mask] = samples\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SusanLi\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\ipykernel_launcher.py:8: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "us = randomiseMissingData(us)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### prop_location_score2, mean imputation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.12443283778729275"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us['prop_location_score2'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "us['prop_location_score2'].fillna((us['prop_location_score2'].mean()), inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### orig_destination_distance, Impute with median"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "us['orig_destination_distance'].fillna((us['orig_destination_distance'].median()), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "site_id                      0\n",
       "prop_country_id              0\n",
       "prop_starrating              0\n",
       "prop_review_score            0\n",
       "prop_brand_bool              0\n",
       "prop_location_score1         0\n",
       "prop_location_score2         0\n",
       "prop_log_historical_price    0\n",
       "position                     0\n",
       "price_usd                    0\n",
       "promotion_flag               0\n",
       "srch_destination_id          0\n",
       "srch_length_of_stay          0\n",
       "srch_booking_window          0\n",
       "srch_adults_count            0\n",
       "srch_children_count          0\n",
       "srch_room_count              0\n",
       "srch_saturday_night_bool     0\n",
       "orig_destination_distance    0\n",
       "random_bool                  0\n",
       "click_bool                   0\n",
       "booking_bool                 0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3467283, 22)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After basic data cleaning, our USA data set contains over 3.4 million observations and 22 features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aab8d6bd68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.countplot(x='booking_bool',data=us, palette='hls')\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    3369149\n",
       "1      98134\n",
       "Name: booking_bool, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us['booking_bool'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aab8e25e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='click_bool',data=us, palette='hls')\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    3317003\n",
       "1     150280\n",
       "Name: click_bool, dtype: int64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us['click_bool'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Due to the nature of online travel business, both booking rate(2.8%) and click through rate (4.3%) are extremely low. So, the class are very imbalanced."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let's explore other features that presented in the data.\n",
    "\n",
    "search length of stay"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aab744bdd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n, bins, patches = plt.hist(us.srch_length_of_stay, 50, density = 1, facecolor='blue', alpha=0.75)\n",
    "plt.xlabel('Search length of stay')\n",
    "plt.title('Histogram of search_length_of_stay')\n",
    "plt.axis([0, 30, 0, 0.65])\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "srch_length_of_stay\n",
       "1    1639357\n",
       "2     870065\n",
       "3     463313\n",
       "4     228522\n",
       "5     106807\n",
       "dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us.groupby('srch_length_of_stay').size().nlargest(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nothing outlier."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "search aults counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAEWCAYAAACdaNcBAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAHERJREFUeJzt3XucHHWd7vHPIwkKhJtmdJEEg0twuSwKjICrQlA8BtSgu+wx8YoHyfGCxwuuoq7AoriivtTjEcQsYrxyZzGLUfAsiayXsEy4REJAsyAkEslwJ6BA4Nk/6jfaTHqme2Y69KTyvF+veU1X1a+rvl3d80z1r7p+LdtERES9PK3bBUREROcl3CMiaijhHhFRQwn3iIgaSrhHRNRQwj0iooYS7psAScslzeh2Hd0k6Q2SVklaJ2nfbtczmKQZklY/Bdv5raTDOt026ifh3mXN/gAlHS3pZwPTtveyvbjFeqZJsqQJG6nUbvsCcJztSbav7XYxmxpJJ0v6brfrGKnBfwvRvoR7tGUc/NN4HrC8WxtXJX8vscnIi3UT0Hh0L+kASX2SHpB0p6QvlmZXlt/3la6Ll0h6mqR/lHSbpLWSvi1p+4b1vq0su1vSJwdt52RJF0r6rqQHgKPLtn8p6T5JayR9VdKWDeuzpPdI+o2kByV9StJflvs8IOn8xvaDHmPTWiU9XdI6YAvgekn/1eS+kvSlcr/7JS2TtHdZ9nRJX5B0e9lfZ0raqizbUdKlkvol3VtuT2lY72JJp0r6OfAw8HxJz5T0TUl3lPtcMqiW40sdayS9o43n9jWSri37Z5Wkkwctf2vDc/SJQcvmS/p0w3TTriFJM4GPA28sr43ry/yjJd1SnqtbJb25jXqPlbSi3OdGSfuV+XuU/XWfqm7EWYP24zsbpp90NF5eN+8qr5t7JZ1entM9gDOBl5S672tVXzSwnZ8u/gC/BQ4bNO9o4GfN2gC/BN5abk8CDiq3pwEGJjTc738BK4Hnl7YXA98py/YE1gEvA7ak6vZ4rGE7J5fp11MdBGwF7A8cBEwo21sBfKBhewYWANsBewGPAP9etr89cCPw9iH2w5C1Nqx7tyHu+2pgKbADIGAPYKey7MulpmcC2wL/BvxzWfYs4O+ArcuyC4BLGta7GLi9PJYJwETgh8B5wI5l+pDSdgawHjilzD+C6h/Cji2e/xnAX5d9vA9wJ/D6Qc/RwcDTgS+WbQw8R/OBTw9a1+ohXjcnA99tWLYN8ADwgjK9E7BXi1r/Hvgd8OKyn3ejekc1sTx3H6d6Lb0CeLBh3YuBdw7z+jZwaXn+dgH6gZnN2uan/Z8cuY8Pl5QjnvvK0ckZw7R9DNhN0mTb62wvGabtm4Ev2r7F9jrgY8BsVV0sRwH/Zvtnth8FTqT6I2v0S9uX2H7C9h9sL7W9xPZ6278Fvg4cMug+p9l+wPZy4Abg8rL9+4EfAUOdDB2u1lYeowrnvwJke4XtNZIEHAt80PY9th8EPgPMBrB9t+2LbD9clp3a5PHMt73c9npgMnA48C7b99p+zPZPB9VxSpm/kCqYXzBc4bYX2/5V2cfLgHMaajgKuNT2lbYfAT4JPNHG/mjXE8DekrayvaY8Z8N5J/A521e7stL2bVT/8CcBn7X9qO0rqMJ6zghq+azt+2zfDiwCXjSKxxMNEu7jw+tt7zDwA7xnmLbHALsDN0m6WtJrh2n7XOC2hunbqI5An1OWrRpYYPth4O5B91/VOCFp99J18fvSVfMZqsBrdGfD7T80mZ40ilqHVcLkq8DpwJ2S5knaDuihOipf2vCP88dlPpK2lvT10u3xAFXX1g6StmhYfeM+mArcY/veIUq5u/wTGPDwMI+XUsOBkhaVrqH7gXfx5306+Dl6iA2fo1Ep63pj2d4aST+U9Fct7jYV2KBbbKBO243/eG4Ddh5BSb9vuN1yv0VrCfdNjO3f2J4DPBs4DbhQ0jZseNQNcAfV2+YBu1C9rb8TWAM09i9vRdVN8aTNDZr+GnATMN32dlRvwzX6R9N2rS3Z/ort/am6UHYH/gG4i+ofyl4N/zy3tz0QHMdTHVkfWB7PwWV+42Nq3AergGdK2mFkD21Y36fqNppqe3uqPuaB7a+hCtSqKGlrnvwcPUT1z2vAXwyznQ1eH7Yvs/0qqi6Zm4B/aVHrKuAvm8y/A5iqJ59w3oWqC2ekdW5Q5gjaRoOE+yZG0lsk9ZSjpIETTI9T9VM+QdVnPeAc4IOSdpU0iepI+7xydHkh8DpJf6PqJOc/0Tqot6Xqp11XjvLe3bEHNnytw5L04nIEPJEqSP4IPF720b8AX5L07NJ2Z0mvbng8f6A6Cf1M4KThtmN7DVXX0hnlZOxESQcPd582bEv1buCPkg4A3tSw7ELgtZJeVp6jU3jy3+x1wBHlJO9fAB8YZjt3AtMGAljScyTNKgcGj1B1IT3eotazgA9L2r+c8NxN0vOAq6j2+0fKPpkBvA44t6HOvy3vlHajevfZrjuBKRriRHwMLeG+6ZkJLFf1CZL/C8y2/cfSrXIq8PPSBXEQcDbwHaruhlupQu99AKV/9X1Uf4BrqE6AraX6Qx/Kh6nC50Gq0Dyvg49ryFrbsF2p516q7oC7qU4QA3yU6mTfktL18v/5cz/4l6lOFN8FLKHqsmnlrVR96zdR7a/hArUd7wFOkfQg1XmP8wcWlOfovVRH92uoHl/jp2G+A1xPdeL0coZ/Pi4ov++WdA3V3/7xVEfd91D18w/XHYjtC6heY9+neg1cAjyznLOZRXU+4i6qc0Zvs31TueuXgEepgvpbwPeG284gV1B9BPb3ku4awf02e7LzriegHC3fR9Xlcmu364mIscmR+2ZM0uvKW+VtqI50f0V1FBgRm7iE++btSKq35XcA06m6ePJWrsPKRT3rmvy0vGjoqabqIq9mtZ7Z7dpiZNItExFRQzlyj4iooa4NBjV58mRPmzatW5uPiNgkLV269C7bPa3adS3cp02bRl9fX7c2HxGxSZJ0W+tW6ZaJiKilhHtERA0l3CMiaijhHhFRQwn3iIgaSrhHRNRQwj0iooYS7hERNZRwj4iooa5dobqpOvTQ0d930aLO1RERMZwcuUdE1FDCPSKihhLuERE1lHCPiKihhHtERA21DHdJZ0taK+mGYdrMkHRd+a7In3a2xIiIGKl2jtznAzOHWihpB+AMYJbtvYC/70xpERExWi3D3faVwD3DNHkTcLHt20v7tR2qLSIiRqkTfe67AztKWixpqaS3DdVQ0lxJfZL6+vv7O7DpiIhophPhPgHYH3gN8Grgk5J2b9bQ9jzbvbZ7e3pafr9rRESMUieGH1gN3GX7IeAhSVcCLwR+3YF1R0TEKHTiyP0HwMslTZC0NXAgsKID642IiFFqeeQu6RxgBjBZ0mrgJGAigO0zba+Q9GNgGfAEcJbtIT82GRERG1/LcLc9p402nwc+35GKIiJizHKFakREDSXcIyJqKOEeEVFDCfeIiBpKuEdE1FDCPSKihhLuERE1lHCPiKihhHtERA0l3CMiaijhHhFRQwn3iIgaSrhHRNRQwj0iooYS7hERNdQy3CWdLWmtpGG/gEPSiyU9LumozpUXERGj0c6R+3xg5nANJG0BnAZc1oGaIiJijFqGu+0rgXtaNHsfcBGwthNFRUTE2Iy5z13SzsAbgDPbaDtXUp+kvv7+/rFuOiIihtCJE6pfBj5q+/FWDW3Ps91ru7enp6cDm46IiGZafkF2G3qBcyUBTAaOkLTe9iUdWHdERIzCmMPd9q4DtyXNBy5NsEdEdFfLcJd0DjADmCxpNXASMBHAdst+9oiIeOq1DHfbc9pdme2jx1RNRER0RK5QjYiooYR7REQNJdwjImoo4R4RUUMJ94iIGkq4R0TUUMI9IqKGEu4RETWUcI+IqKGEe0REDSXcIyJqKOEeEVFDCfeIiBpKuEdE1FDCPSKihhLuERE11DLcJZ0taa2kG4ZY/mZJy8rPLyS9sPNlRkTESLRz5D4fmDnM8luBQ2zvA3wKmNeBuiIiYgza+Zq9KyVNG2b5LxomlwBTxl5WRESMRaf73I8BfjTUQklzJfVJ6uvv7+/wpiMiYkDHwl3SoVTh/tGh2tieZ7vXdm9PT0+nNh0REYO07JZph6R9gLOAw23f3Yl1RkTE6I35yF3SLsDFwFtt/3rsJUVExFi1PHKXdA4wA5gsaTVwEjARwPaZwInAs4AzJAGst927sQqOiIjW2vm0zJwWy98JvLNjFUVExJjlCtWIiBpKuEdE1FDCPSKihhLuERE1lHCPiKihhHtERA0l3CMiaijhHhFRQwn3iIgaSrhHRNRQwj0iooYS7hERNZRwj4iooYR7REQNJdwjImoo4R4RUUMtw13S2ZLWSrphiOWS9BVJKyUtk7Rf58uMiIiRaOfIfT4wc5jlhwPTy89c4GtjLysiIsaiZbjbvhK4Z5gmRwLfdmUJsIOknTpVYEREjFwn+tx3BlY1TK8u8zYgaa6kPkl9/f39Hdh0REQ004lwV5N5btbQ9jzbvbZ7e3p6OrDpiIhophPhvhqY2jA9BbijA+uNiIhR6kS4LwDeVj41cxBwv+01HVhvRESM0oRWDSSdA8wAJktaDZwETASwfSawEDgCWAk8DLxjYxUbERHtaRnutue0WG7gvR2rKCIixixXqEZE1FDCPSKihhLuERE1lHCPiKihhHtERA0l3CMiaijhHhFRQwn3iIgaSrhHRNRQwj0iooYS7hERNZRwj4iooYR7REQNJdwjImoo4R4RUUMJ94iIGmor3CXNlHSzpJWSTmiyfBdJiyRdK2mZpCM6X2pERLSrZbhL2gI4HTgc2BOYI2nPQc3+ETjf9r7AbOCMThcaERHta+fI/QBgpe1bbD8KnAscOaiNge3K7e2BOzpXYkREjFQ74b4zsKphenWZ1+hk4C3lC7QXAu9rtiJJcyX1Serr7+8fRbkREdGOdsJdTeZ50PQcYL7tKcARwHckbbBu2/Ns99ru7enpGXm1ERHRlnbCfTUwtWF6Cht2uxwDnA9g+5fAM4DJnSgwIiJGrp1wvxqYLmlXSVtSnTBdMKjN7cArASTtQRXu6XeJiOiSluFuez1wHHAZsILqUzHLJZ0iaVZpdjxwrKTrgXOAo20P7rqJiIinyIR2GtleSHWitHHeiQ23bwRe2tnSIiJitHKFakREDSXcIyJqKOEeEVFDCfeIiBpKuEdE1FDCPSKihhLuERE1lHCPiKihhHtERA0l3CMiaijhHhFRQwn3iIgaSrhHRNRQwj0iooYS7hERNdRWuEuaKelmSSslnTBEm/8p6UZJyyV9v7NlRkTESLT8sg5JWwCnA6+i+j7VqyUtKF/QMdBmOvAx4KW275X07I1VcEREtNbOkfsBwErbt9h+FDgXOHJQm2OB023fC2B7bWfLjIiIkWgn3HcGVjVMry7zGu0O7C7p55KWSJrZqQIjImLk2vkOVTWZN/jLrycA04EZwBTgPyTtbfu+J61ImgvMBdhll11GXGxERLSnnSP31cDUhukpwB1N2vzA9mO2bwVupgr7J7E9z3av7d6enp7R1hwRES20E+5XA9Ml7SppS2A2sGBQm0uAQwEkTabqprmlk4VGRET7Woa77fXAccBlwArgfNvLJZ0iaVZpdhlwt6QbgUXAP9i+e2MVHRERw2unzx3bC4GFg+ad2HDbwIfKT0REdFlb4T7eHHro2O6/aFFn6oiIGK8y/EBERA0l3CMiaijhHhFRQwn3iIgaSrhHRNRQwj0iooYS7hERNZRwj4iooYR7REQNJdwjImoo4R4RUUMJ94iIGkq4R0TUUMI9IqKGEu4RETXUVrhLminpZkkrJZ0wTLujJFlSb+dKjIiIkWoZ7pK2AE4HDgf2BOZI2rNJu22B/wNc1ekiIyJiZNo5cj8AWGn7FtuPAucCRzZp9yngc8AfO1hfRESMQjvhvjOwqmF6dZn3J5L2BabavnS4FUmaK6lPUl9/f/+Ii42IiPa0E+5qMs9/Wig9DfgScHyrFdmeZ7vXdm9PT0/7VUZExIi0E+6rgakN01OAOxqmtwX2BhZL+i1wELAgJ1UjIrqnnXC/GpguaVdJWwKzgQUDC23fb3uy7Wm2pwFLgFm2+zZKxRER0VLLcLe9HjgOuAxYAZxve7mkUyTN2tgFRkTEyE1op5HthcDCQfNOHKLtjLGXFRERY5ErVCMiaijhHhFRQwn3iIgaSrhHRNRQwj0iooYS7hERNZRwj4iooYR7REQNJdwjImoo4R4RUUMJ94iIGkq4R0TUUMI9IqKGEu4RETWUcI+IqKGEe0REDbUV7pJmSrpZ0kpJJzRZ/iFJN0paJunfJT2v86VGRES7Woa7pC2A04HDgT2BOZL2HNTsWqDX9j7AhcDnOl1oRES0r50j9wOAlbZvsf0ocC5wZGMD24tsP1wmlwBTOltmRESMRDvhvjOwqmF6dZk3lGOAHzVbIGmupD5Jff39/e1XGRERI9JOuKvJPDdtKL0F6AU+32y57Xm2e2339vT0tF9lRESMyIQ22qwGpjZMTwHuGNxI0mHAJ4BDbD/SmfIiImI02jlyvxqYLmlXSVsCs4EFjQ0k7Qt8HZhle23ny4yIiJFoGe621wPHAZcBK4DzbS+XdIqkWaXZ54FJwAWSrpO0YIjVRUTEU6CdbhlsLwQWDpp3YsPtwzpcV0REjEGuUI2IqKGEe0REDSXcIyJqqK0+94jROvTQ0d930aLO1RGxucmRe0REDeXIfTORI+iIzUuO3CMiaijhHhFRQwn3iIgaSrhHRNRQwj0iooYS7hERNZRwj4iooYR7REQNJdwjImoo4R4RUUNthbukmZJulrRS0glNlj9d0nll+VWSpnW60IiIaF/LsWUkbQGcDryK6suyr5a0wPaNDc2OAe61vZuk2cBpwBs3RsERT4VujcWTMYCiU9oZOOwAYKXtWwAknQscCTSG+5HAyeX2hcBXJcm2O1hrRMST5J/h0NoJ952BVQ3Tq4EDh2pje72k+4FnAXc1NpI0F5hbJtdJunk0RQOTB697JKTR3rOlYevaiNttx6j32Uaue8i6sr+aqt3+2sjquL+e106jdsK92S4YfETeThtszwPmtbHN4QuS+mz3jnU9nTZe64LxW1vqGpnUNTKbc13tnFBdDUxtmJ4C3DFUG0kTgO2BezpRYEREjFw74X41MF3SrpK2BGYDCwa1WQC8vdw+Crgi/e0REd3Tslum9KEfB1wGbAGcbXu5pFOAPtsLgG8A35G0kuqIffbGLJoOdO1sJOO1Lhi/taWukUldI7PZ1qUcYEdE1E+uUI2IqKGEe0REDW1S4S7pbElrJd3Q7VoaSZoqaZGkFZKWS3p/t2sCkPQMSf8p6fpS1z91u6ZGkraQdK2kS7tdywBJv5X0K0nXSerrdj0DJO0g6UJJN5XX2UvGQU0vKPtp4OcBSR/odl0Akj5YXvM3SDpH0jO6XROApPeXmpZv7H21SfW5SzoYWAd82/be3a5ngKSdgJ1sXyNpW2Ap8PpBQzR0oy4B29heJ2ki8DPg/baXdLOuAZI+BPQC29l+bbfrgSrcgV7b4+qCHEnfAv7D9lnlU2tb276v23UNKMOU/A440PZtXa5lZ6rX+p62/yDpfGCh7fldrmtv4Fyqq/4fBX4MvNv2bzbG9japI3fbVzIOPz9ve43ta8rtB4EVVFftdpUr68rkxPIzLv6bS5oCvAY4q9u1jHeStgMOpvpUGrYfHU/BXrwS+K9uB3uDCcBW5bqbrdnw2pxu2ANYYvth2+uBnwJv2Fgb26TCfVNQRsTcF7iqu5VUStfHdcBa4Ce2x0VdwJeBjwBPdLuQQQxcLmlpGS5jPHg+0A98s3RjnSVpm24XNchs4JxuFwFg+3fAF4DbgTXA/bYv725VANwAHCzpWZK2Bo7gyReIdlTCvYMkTQIuAj5g+4Fu1wNg+3HbL6K6sviA8tawqyS9Flhre2m3a2nipbb3Aw4H3lu6ArttArAf8DXb+wIPARsMvd0tpZtoFnBBt2sBkLQj1WCGuwLPBbaR9JbuVgW2V1CNmPsTqi6Z64H1G2t7CfcOKX3aFwHfs31xt+sZrLyNXwzM7HIpAC8FZpX+7XOBV0j6bndLqti+o/xeC/wrVf9ot60GVje867qQKuzHi8OBa2zf2e1CisOAW233234MuBj4my7XBIDtb9jez/bBVF3MG6W/HRLuHVFOXH4DWGH7i92uZ4CkHkk7lNtbUb3ob+puVWD7Y7an2J5G9Xb+CttdP7KStE05IU7p9vgfVG+lu8r274FVkl5QZr2SJw+53W1zGCddMsXtwEGSti5/m6+kOg/WdZKeXX7vAvwtG3G/tTMq5Lgh6RxgBjBZ0mrgJNvf6G5VQHUk+lbgV6V/G+Djthd2sSaAnYBvlU8yPA043/a4+djhOPQc4F+rPGAC8H3bP+5uSX/yPuB7pQvkFuAdXa4HgNJ3/Crgf3e7lgG2r5J0IXANVbfHtYyfYQgukvQs4DHgvbbv3Vgb2qQ+ChkREe1Jt0xERA0l3CMiaijhHhFRQwn3iIgaSrhHRNRQwj06TtInyqh3y8pogQdu5O2ta92q7XUtljTsFxdLOlnSh8vtoyU9t1PbHytJ0yS9qdt1RPcl3KOjylC0rwX2s70P1YVTqzqw3vF6TcbRVJe4jxfTgIR7JNyj43YC7rL9CIDtuwYu6Ze0v6SflkG5LitDJSPpWElXl3HnLyoXxiBpvqQvSloEnCZpkqRvlvHWl0n6u4GNSjq13H+JpOcMLkrSAZJ+UQbe+sXA1Z6StpJ0blnfecBWDfdZ13D7KEnzB63zKKohi79X3qFsJemzkm4s6/tCkzqaPgZJc8q8GySd1qqGsm++Uh7LLaUWgM8CLy/1fLCN5ytqKuEenXY5MFXSryWdIekQ+NPYO/8POMr2/sDZwKnlPhfbfrHtF1JdJn5Mw/p2Bw6zfTzwSaoR/v66vCu4orTZhmoo1RcCVwLHNqnrJuDgMvDWicBnyvx3Aw+X9Z0K7N/uA7V9IdAHvLkMzrYV1RCue5X1fbrJ3TZ4DKVb5zTgFcCLgBdLen0bJewEvIzqndJny7wTqMZ9f5HtL7X7WKJ+xutb3dhElS8G2R94OXAocJ6kE6hCcG/gJ+Xy/i2ohmMF2FvSp4EdgEnAZQ2rvMD24+X2YVRj0Qxsa+DS7UeBgWEVllJdDj/Y9lRDMUynGtZ3Ypl/MPCVsr5lkpaN5nEXDwB/BM6S9MOGmhpt8BjKyJOLbfcDSPpeqeuSFtu7xPYTwI3N3q3E5i3hHh1XwngxsFjSr4C3U4XuctvNvh5uPtU3V10v6Wiq8YMGPNRwWzT/spHH/OdxNB6n+ev6U8Ai229QNeb+4saSh3ooDbdbfk2b7fWSDqAaqGo2cBzV0XijZo9Bw612mBoeaXMdsRlKt0x0lKrv1ZzeMOtFwG3AzUBPOeGKpImS9ipttgXWlK6bNw+z+supAnNgWzuOoLTtqb4GDqqToAOuHNimqrHu92lYdqekPSQ9jaG/MefBUv/AeP7blwHjPkD12Nt5DFcBh0iaXAZ5m0P1LT3t1tC0nti8Jdyj0yZRdX/cWLo49gROtv0ocBTVidHrgev48xjbn6QKuJ8w/JDEnwZ2LCcdr6fq9mnX54B/lvRzqi6hAV8DJpVaPwL8Z8OyE6i6Vq7gz11Ig80HzlQ1Gui2wKVlXT8Fmp3Q3OAx2F4DfAxYRPUFDtfY/sEIami0DFhfTi7nhOpmLKNCRkTUUI7cIyJqKOEeEVFDCfeIiBpKuEdE1FDCPSKihhLuERE1lHCPiKih/wZcB0Mxpb7F+AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aab74c2208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n, bins, patches = plt.hist(us.srch_adults_count, 20, density = 1, facecolor='blue', alpha=0.75)\n",
    "plt.xlabel('Search adults count')\n",
    "plt.title('Histogram of search_adults_count')\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "srch_adults_count\n",
       "2    6494969\n",
       "1    2315541\n",
       "4     481440\n",
       "3     475287\n",
       "6      63323\n",
       "dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('srch_adults_count').size().nlargest(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The most common search adults count is 2-adults, makes sense."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "property star rating"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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A7NL8LGBbkzZXRcR/RcS9wN0UYW9mZl1QJdxvA+ZIOlTSnsBpwKqGNv8MHA8gqYdimOaeOgs1M7Pq2oZ7ROwEzgauATYBKyNig6QLJJ2cml0DPChpIzAAfCgiHpyoos3MbHRt3woJEBGrgdUNy84rTQfw/vQwM7Mu8ydUzcwy5HA3M8uQw93MLEMOdzOzDDnczcwy5HA3M8uQw93MLEMOdzOzDDnczcwy5HA3M8uQw93MLEMOdzOzDDnczcwy5HA3M8uQw93MLEOVwl3SAkl3S9os6dxR2p0qKST111eimZl1qm24S5oGXAycCMwFFkma26TdfsB7gVvrLtLMzDpT5cx9HrA5Iu6JiKeAFcDCJu0+AXwa+GWN9ZmZ2RhUCfeZwNbS/FBa9ixJRwOzI+Lq0TqStETSoKTB4eHhjos1M7NqqoS7miyLZ1dKewCfAz7QrqOIWBoR/RHR39vbW71KMzPrSJVwHwJml+ZnAdtK8/sBrwSul7QFOAZY5YuqZmbdUyXcbwPmSDpU0p7AacCqkZUR8WhE9EREX0T0AbcAJ0fE4IRUbGZmbbUN94jYCZwNXANsAlZGxAZJF0g6eaILNDOzzk2v0igiVgOrG5ad16Lt/PGXZWZm4+FPqJqZZcjhbmaWIYe7mVmGHO5mZhlyuJuZZcjhbmaWIYe7mVmGHO5mZhlyuJuZZcjhbmaWIYe7mVmGHO5mZhlyuJuZZcjhbmaWIYe7mVmGKoW7pAWS7pa0WdK5Tda/X9JGSXdJulbSS+sv1czMqmob7pKmARcDJwJzgUWS5jY0uwPoj4gjgSuAT9ddqJmZVVflzH0esDki7omIp4AVwMJyg4gYiIgn0+wtFF+ibWZmXVIl3GcCW0vzQ2lZK2cB3222QtISSYOSBoeHh6tXaWZmHanyHapqsiyaNpROB/qB45qtj4ilwFKA/v7+pn2YmU0Fxx8/9ucODNRXRytVwn0ImF2anwVsa2wk6QTgfwPHRcSv6inPzMzGosqwzG3AHEmHStoTOA1YVW4g6WjgH4CTI2J7/WWamVkn2oZ7ROwEzgauATYBKyNig6QLJJ2cml0E7At8U9I6SatadGdmZpOgyrAMEbEaWN2w7LzS9Ak112VmZuPgT6iamWWo0pn7c814rlLD5FypNjPrJp+5m5llyOFuZpYhh7uZWYYc7mZmGXK4m5llyOFuZpYhh7uZWYYc7mZmGXK4m5llyOFuZpYhh7uZWYYc7mZmGXK4m5llyOFuZpahSuEuaYGkuyVtlnRuk/XPk/SNtP5WSX11F2pmZtW1DXdJ04CLgROBucAiSXMbmp0FPBwRLwc+B1xYd6FmZlZdlS/rmAdsjoh7ACStABYCG0ttFgLnp+krgC9IUkREjbXu1vwFJWbWiSrhPhPYWpofAl7Tqk1E7JT0KHAQ8EC5kaQlwJI0u0PS3WMpGuhp7LsT0lif2VXe5w5M0f0F73NHpuo+S+P6fX5plUZVwr3Z4Ws8I6/ShohYCiytsM3RC5IGI6J/vP1MJd7n3YP3efcwGftc5YLqEDC7ND8L2NaqjaTpwAHAQ3UUaGZmnasS7rcBcyQdKmlP4DRgVUObVcA70vSpwHUebzcz6562wzJpDP1s4BpgGnB5RGyQdAEwGBGrgMuAr0raTHHGftpEFk0NQztTkPd59+B93j1M+D7LJ9hmZvnxJ1TNzDLkcDczy9CUC/d2t0LIjaTLJW2XtL7btUwWSbMlDUjaJGmDpPd1u6aJJun5kv5N0p1pnz/e7Zomg6Rpku6QdHW3a5kMkrZI+pGkdZIGJ3RbU2nMPd0K4SfA6ynefnkbsCgiNo76xClM0v8EdgBfiYhXdrueySDpYODgiLhd0n7AWuBNmb/OAvaJiB2SZgA3AO+LiFu6XNqEkvR+oB/YPyLe2O16JpqkLUB/RIz5A4lVTbUz92dvhRARTwEjt0LIVkSsYTf7zEBE3B8Rt6fpx4FNFJ+CzlYUdqTZGekxdc68xkDSLOANwKXdriVHUy3cm90KIetf+t1dusPo0cCt3a1k4qUhinXAduAHEZH7Pn8e+F/AM90uZBIF8H1Ja9PtWCbMVAv3Src5sDxI2hf4FnBORDzW7XomWkQ8HRFHUXwKfJ6kbIfhJL0R2B4Ra7tdyyQ7NiJ+m+Iuu3+Rhl0nxFQL9yq3QrAMpHHnbwFfj4gru13PZIqIR4DrgQVdLmUiHQucnMagVwC/L+lr3S1p4kXEtvTvduDbFEPNE2KqhXuVWyHYFJcuLl4GbIqIz3a7nskgqVfSgWl6L+AE4MfdrWriRMRHImJWRPRR/B5fFxGnd7msCSVpn/QGASTtA/whMGHvgptS4R4RO4GRWyFsAlZGxIbuVjWxJC0HbgZeIWlI0lndrmkSHAu8neJsbl16nNTtoibYwcCApLsoTmJ+EBG7xdsDdyMvBm6QdCfwb8C/RMT3JmpjU+qtkGZmVs2UOnM3M7NqHO5mZhlyuJuZZcjhbmaWIYe7mVmGHO42ISQ9nd7CuF7SNyXtPcnbny/ptTX0c9Rkvg1T0jnlYyVp9cj738064XC3ifKLiDgq3cnyKeDPyitVmJCfv/Ql7fOBcYc7cBTQUbin7bda126/zwGeDfeIOCl9YtWsIw53mwz/CrxcUl+6R/sXgduB2ZIWpftbr5d04cgTJO2Q9BlJt0u6VlJvWv4ySd9LN176V0mHp+XLJH1W0gDwDYr/TP4y/fXwe5LuTbc0QNL+6b7aM8pFSnpzquNOSWvSp6AvAN6S+nmLpHmSbkr3IL9J0ivScxenv1C+A3y/od9m+/0lSYPle7dLei/wEooPMw2kZVsk9ZT6+HJ6zvfTJ1mR9GpJd0m6WdJF2o3u/W+jiAg//Kj9AexI/04HrgL+HOijuAPgMWndS4CfAr2p3XUU922H4oZwb0vT5wFfSNPXAnPS9GsoPrYOsAy4GpiW5s8HPliq5x9LfS8BPtOk5h8BM9P0genfxSPbTvP7A9PT9AnAt0rthoAXNun31/Y7LXth+ncaxX1kjkzzW4CeUrstQE/qYydwVFq+Ejg9Ta8HXpum/y+wvtuvvx/df/jM3SbKXun2tYMUAX5ZWn5f/PcXULwauD4ihqO4tcTXgZG75D1DcQYO8DXgdekuka8Fvpn6/geKj+2P+GZEPN2inkuBM9P0mRRh3+hGYJmkd1GEbjMHpO2vBz4HHFFa94OIaHXv/fJ+A/yJpNuBO1Ifc1s8r+zeiFiXptcCfWk8fr+IuCkt/6cK/dhuoOXYoNk4/SKK29c+q7gfGE+UF3XQX1AMIz7S2G/JEy2WExE3pqGN4yjO7ncZuoiIP5P0GoovkFgnqdl2PgEMRMQpKu41f32V7ZfXSToU+CDw6oh4WNIy4PmjPHfEr0rTTwN70dkxtN2Iz9ytm24FjktjytOARcAP07o9gFPT9FuBG6K4p/u9kt4Mz16cfFWLvh8H9mtY9hVgOc3P2pH0soi4NSLOAx6guL10Yz8HAP+ZphdX2std7U8R9o9KejHFvb1Hq7uliHgYeFzSMWnRaWOsyTLjcLeuiYj7gY8AA8CdwO0RcVVa/QRwhKS1wO9TXNgEeBtwVrqz3gZaf83id4BTRi6opmVfB15AEfDNXDRycRdYk2oaAOaOXFAFPg18StKNtB66abffd1IMx2wALqcYDhqxFPjuyAXVis4Clkq6meJM/tGx1GV58V0h7TlJ0o6I2LfmPk8FFkbE2+vst9sk7Rvp+1clnUvx5eLv63JZ1mUec7fdgqS/pxj+yPG+8G+Q9BGK3+f7GPtwkWXEZ+5mZhnymLuZWYYc7mZmGXK4m5llyOFuZpYhh7uZWYb+PxTB+Lr70ulBAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aab758c358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n, bins, patches = plt.hist(us.prop_starrating, 20, density = 1, facecolor='blue', alpha=0.75)\n",
    "plt.xlabel('Property star rating')\n",
    "plt.title('Histogram of prop_star_rating')\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The most common property star rating is 3 stars. Good to know, I would have thought higher."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "prop_brand_bool\n",
       "0     925574\n",
       "1    2541709\n",
       "dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us.groupby('prop_brand_bool').size()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "More than 73% of the properties are brand properties. It does make sense since we are talking about US hotels and US travelers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "srch_saturday_night_bool\n",
       "0    1589888\n",
       "1    1877395\n",
       "dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us.groupby('srch_saturday_night_bool').size()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Over 54% of searches contain staying at Saturday."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Price USD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aab756c630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(style=\"ticks\", palette=\"pastel\")\n",
    "\n",
    "ax = sns.boxplot(x=\"click_bool\", y=\"price_usd\", hue=\"click_bool\", data=us)\n",
    "ax.set_ylim([0, 200]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>click_bool</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3317003.0</td>\n",
       "      <td>159.784904</td>\n",
       "      <td>1443.170964</td>\n",
       "      <td>0.04</td>\n",
       "      <td>82.0</td>\n",
       "      <td>119.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>505455.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>150280.0</td>\n",
       "      <td>144.195764</td>\n",
       "      <td>845.042969</td>\n",
       "      <td>0.06</td>\n",
       "      <td>82.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>162.0</td>\n",
       "      <td>172761.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                count        mean          std   min   25%    50%    75%  \\\n",
       "click_bool                                                                 \n",
       "0           3317003.0  159.784904  1443.170964  0.04  82.0  119.0  178.0   \n",
       "1            150280.0  144.195764   845.042969  0.06  82.0  112.0  162.0   \n",
       "\n",
       "                 max  \n",
       "click_bool            \n",
       "0           505455.0  \n",
       "1           172761.0  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us.groupby('click_bool')['price_usd'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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F6dOnaWxsZOfOnQwfPpxu3boREBDA4cOHAdi+fTvDhw9vcRkhISFEREQ4fYWH37y3ExARcTdDWxr5+fmsX7+euro6YmNjmT17NvPmzWPixIlERUUZWlFAQADLli3j0Ucfpa6ujhEjRnDfffcBsGLFCjIzM6mpqaFfv36kpKRc/ycSERGXMVQaGzduJDc3lylTptCpUyfy8/OZPn06EydO/MH37t692/F9TEwMBQUFzebp06cPW7ZsuYbYIiLiCYZ2T/n4+NC+fXvHdNeuXfH19XVZKBER8U6GSqNDhw4cP37ccVZTQUEBP/vZz1waTEREvI+h3VMZGRk89thjnDlzhnvuuYeAgADWrFnj6mwiIuJlDJVGr1692Lp1K2fOnKGxsZGePXvi5+e2SzxERMRLGNo99eGHH/Lggw/Sq1cvTCYTI0aMcDrtVkREbg6GSmP58uWO26P37t2bV1999aq3SxcRkRuTodKw2Wz069fPMd2vXz/q6+tdFkpERLyTodJo27YtH3zwgWN6//79BAUFuSyUiIh4J0NHsxcsWMCcOXMcB799fHxYvXq1S4OJiIj3MVQa/fv3Z+/evXz++ef4+voSFRWFv7+/q7OJiIiXuWppbN++nXHjxvH66687jRcVFQHwyCOPuC6ZiIh4nauWxunTpwH4/PPP3RJGRES821VLY+7cuQB07tyZP/zhD24JJCIi3svQMY29e/fe8KVx8etzHNuz2WPrt9V+A0CbwHYey3Dx63MQ3M1j6xcR72eoNCIiIpg2bRrR0dG0a/eff2o3yjGNbt08/4+yovoiAKGhHTwXIribV/wsRMR7GSqNDh0u/yM7duwYvr6+BAcHuzSUu40bN87TERw3gJw9e7aHk4iIfD9DpTF9+nTS09M5fvw4ANHR0SxfvtylwUREWmKpqeeNQ5UeW39NfSMA7f0980whS0093Tp6ZNXANdwafeLEiYwfPx673U5ubi4LFixodiquiIgrecPu04sVFQB06HirR9bfraNnfw6GSuPSpUs8/PDDjunk5GTy8vKua4VvvvkmmzZtckyXlZUxbtw4Ll26xOHDh2nbti0AaWlpxMbGXtc6ROTGpF3JnmeoNHr27Mnf//53oqOjgcvXbURERFzXCh966CEeeughAE6ePMmcOXNIS0sjNTWVTZs2ERYWdl3LFRER1zNUGhUVFSQnJ3PHHXfg5+fHp59+SmhoKGazGYAdO3Zc18r/+7//m3nz5tG2bVsqKirIyMjAYrEQGxtLWloaPj6G7qcoIiJuYqg0nnjiiVZfcVFREbW1tYwZM4bS0lKGDh1KVlYWwcHBzJw5ky1btjBx4kSn91itVqxWq9NYZaXnDoiJiNxsDJXGXXfd1eor/tOf/uS4zqN79+689NJLjteSk5PZtm1bs9LYsGED2dnZrZ5FRESM8ciDvuvr6zl48CDLli0D4MSJE5SUlBAXFweA3W5v8RnkqampJCQkOI1VVlaSlJTk+tAiIuKZ0jhx4gQ9evRwPMjJbrezZMkShg4dSlBQELm5uc3KASAkJISQkBB3xxURkX/zSGmUlpYSHh7umO7Tpw8zZsxg0qRJNDQ0MHr0aOLj4z0RTURErsIjpXH//fdz//33O40lJSVpN5OIiJfTOa0iImKYSkNERAxTaYiIiGEqDRERMUylISIihqk0RETEMJWGiIgYptIQERHDVBoiImKYSkNERAxTaYiIiGEqDRERMUylISIihqk0RETEMJWGiIgYptIQERHDVBoiImKYSkNERAzzyONek5OTuXDhAn5+l1e/aNEizpw5w8svv0xDQwOpqal69KuIiBdye2nY7XZKSkrYs2ePozQsFgvz5s0jPz8ff39/EhMTGTJkCLfddpu744mIyFW4vTS+/PJLAKZNm8bXX3/NxIkTadeuHUOHDqVDhw4AxMXFUVhYSFpamrvjiYjIVbi9NKxWKzExMTzzzDPYbDZSUlIYM2YMoaGhjnnCwsI4evRoi++1Wq1OY5WVlS7PLD89NpuNsrIyamtrPR3FKwQGBhIREUGbNm08HUV+4txeGgMHDmTgwIGO6QkTJrB06VJmzZrlGLPb7ZhMpmbv3bBhA9nZ2W7JKT9tZWVlBAcH06NHjxZ/l24mdrudr776irKyMqKiojwdR37i3F4ahw4dwmazERMTA1z+he7WrRtVVVWOeaqqqggLC2v23tTUVBISEpzGKisrddBcmqmtrVVh/JvJZKJTp05Of2Mi18vtp9xWV1ezfPly6urqqKmpYevWrbzwwgvs37+fCxcucOnSJd577z2GDx/e7L0hISFEREQ4fYWHh7v7I8hPhArjP/SzkNbi9i2NkSNHcuTIEX7zm9/Q1NTE5MmTGTRoEPPmzSMlJQWbzcaECRO488473R1NRER+gEeu03j88cd5/PHHncbMZjNms9kTceQmkZ+fz8mTJ3nqqaeu6/2rV6/mlltuYcqUKY6xXbt2UVpaytSpU390vo8++oicnBxefPHF617Gj/2MIj/EI6UhcqMYNWqUpyOIuJVuIyI3lU8//ZSHHnoIs9nMhx9+SEVFBSkpKTzwwAPMnDmTCxcuAPDnP/+Z+Ph4zGYza9eudVpGdXU148ePp6ioiPz8fJ5//nnKysqYNGkSaWlpxMXF8fzzzwOXD8jPnj0bs9nMwoULiY2NvWq+8vJypkyZQnx8PDt37gQun2o+a9YszGYzycnJnDlzBoD9+/fzm9/8BrPZzHPPPUdTU1Nr/7hEmlFpyE3lq6++YuPGjaxevZqFCxeyaNEiEhMTKSgoYPjw4axYsYJz587x4osvsmnTJt566y327t3LoUOHAGhoaOCxxx5j+vTpDBs2zGnZx44dIyMjg4KCAt555x0sFgs5OTn8/Oc/Z8eOHfTt25fGxsar5jt79iyrV69m48aNrFy5kurqalavXk10dDQ7duxg+vTpPPPMM9TX15OZmcnq1aspKCjg/PnzFBQUuOznJnKFSkNuKqNGjSIwMJAePXrQvn179uzZw5gxYwAYN24cBw8epLi4mLvuuosOHTrg7+/PmDFjOHDgAABr166lrKyMuLi4ZsuOjIzk1ltvJSAggIiICKxWKwcPHuS+++4DMHTMLiYmhltuuYVbbrmFfv36ceLECQ4fPswDDzwAwIgRI/jiiy/48ssviYyMpHv37phMJsxmMwcPHmytH5PI91JpyE3Fx+c/v/J2ux1/f3+n6cbGxma7ea6MA8TGxjJgwAA2b97cbNnfvtraZDJht9vx8fHBbrcbzufr6+u0Xj8/v2ZbJzabrdnYtzOKuJJKQ24q77//PvX19fzzn//EZrNx991388477wBQUFDAwIED+eUvf8mHH37I119/TX19PYWFhY67GNx+++384Q9/YN26dY7jH1czePBg/vKXvwDw17/+9Qfn/+ijj7BarZw/f54TJ07Qu3dvBg8e7Nj1tHfvXqKioujVqxclJSWUlpZit9vZuXOn050WRFxFZ0/JTSUsLIzExEQaGxtZvHgxHTt2JCMjgzVr1tC5c2eef/55unTpwqOPPkpycjI2m40xY8Zwzz338PHHHwPQpUsXHn74Yf73f/+XQYMGXXV9kydPJj09nXHjxnH77bcTEBBw1fkjIyOZMWMGNTU1ZGRk0K5dO9LS0pg/fz4FBQUEBQWxZMkSAgMDefbZZ0lLS6Ouro677rqLBx98UMc1xOVM9mvZdvZCZWVljBo1il27dhEREeHpONdtzZo1AMyePdvDSW4Mx48fp2/fvp6OwZ49ewgJCWHQoEHs3r2bN998k5dfftkjWbzlZ/JTd6P8rV7v/05taYi4UGRkJE888QQ2m422bduydOlSVqxYwd/+9rdm82ZlZREdHe2BlCLGqTREXKhnz57k5+c7jT3xxBM88cQTHkok8uPoQLiIiBim0hAREcNUGiIiYphKQ0REDNOBcJEWrH3tj1RXX2z15QYHBzFz+rQfnG/Hjh28/PLLNDQ0kJqaqqdTitdQaYi0oLr6Ij3ufrjVl1vy/3J/cB6LxcKqVavIz8/H39+fxMREhgwZwm233dbqeUSulXZPiXiZoqIihg4dSocOHQgKCiIuLo7CwkJPxxIBVBoiXufcuXOEhoY6psPCwrBYLB5MJPIfHtk9lZ2d7bhJ3IgRI0hPT2f+/PkcPnyYtm3bApCWlvaDD6wRuRE1NTVhMpkc03a73WlaxJPcXhpFRUXs27ePrVu3YjKZmD59On/5y18oLi5m06ZNhIWFuTuSiFcJDw93PPQJoKqqSn8X4jXcvnsqNDSUp59+Gn9/f9q0aUOvXr2oqKigoqKCjIwMzGYzL774oh5dKTetYcOGsX//fi5cuMClS5d47733GD58uKdjiQAe2NLo3bu34/uSkhLeeecdcnJyOHDgAFlZWQQHBzNz5ky2bNnCxIkTnd5rtVqxWq1OY5WVlW7JLeIuXbp0Yd68eaSkpGCz2ZgwYQJ33nmnp2OJAB485fbkyZPMnDmT9PR0evbsyUsvveR4LTk5mW3btjUrjQ0bNpCdne3uqHITCg4OMnR67PUs1wiz2Wzo8bAi7uaR0jh8+DBz584lIyODsWPHcuLECUpKShzPXb7ymMvvSk1NJSEhwWmssrJSFz5JqzNyAZ7IzcjtpXH27FnmzJnDqlWriImJAS6XxJIlSxg6dChBQUHk5uY2KweAkJAQQkJC3B1ZRET+ze2lsX79eurq6li2bJljLDExkRkzZjBp0iQaGhoYPXo08fHx7o4mIiI/wO2lkZmZSWZmZouvaTeTiIh30xXhIiJimEpDREQMU2mIiIhhujW6SAtef/Vlvqm2/vCM16hdcAiPzJhlaN6amhoSExN55ZVXiIiIaPUsItdDpSHSgm+qrUzpZ+xCvGux6ZixIjpy5AiZmZmUlJS0egaRH0O7p0S8UF5eHllZWbpRoXgdbWmIeKHFixd7OoJIi7SlISIihqk0RETEMJWGiIgYpmMaIi1oFxxi+Eyna12uyE+ZSkOkBUavpXC13bt3ezqCiBPtnhIREcNUGiIiYphKQ0REDFNpyA3Lbrd7OoLX0M9CWotKQ25IgYGBfPXVV/pnyeXC+OqrrwgMDPR0FLkB6OwpuSFFRERQVlZGVVWVp6N4hcDAQN0pV1qFSkNuSG3atCEqKsrTMURuOF61e2rHjh3cf//9jB49mpycHE/HERGR7/CaLQ2LxcKqVavIz8/H39+fxMREhgwZwm233ebpaCIi8m9eUxpFRUUMHTqUDh06ABAXF0dhYSFpaWmOeaxWK1ar860dysvLAaisrHRf2BZ88sknHDly5Lrfb7FYAFi2bNmPytG/f39++ctf/qhliNyofuzfKbTO36o3/J1e+Z/Z2Nh4Te/zmtI4d+4coaGhjumwsDCOHj3qNM+GDRvIzs5u8f1JSUkuzSciciOqqqoiMjLS8PxeUxpNTU2YTCbHtN1ud5oGSE1NJSEhwWmsvr6e0tJSevToga+vr1uy3sgqKytJSkoiJyeH8PBwT8cRcdDvZutqbGykqqqKX/ziF9f0Pq8pjfDwcA4dOuSYrqqqavaoy5CQEEJCmt8ltGfPni7Pd7MJDw/XKZrilfS72XquZQvjCq85e2rYsGHs37+fCxcucOnSJd577z2GDx/u6VgiIvItXrOl0aVLF+bNm0dKSgo2m40JEyZw5513ejqWiIh8i9eUBoDZbMZsNns6hoiIfA+v2T0l3iEkJIS0tLQWjx2JeJJ+N72Dya47uomIiEHa0hAREcNUGiIiYphKQxx0w0jxZjU1NcTHx1NWVubpKDc1lYYA/7lh5ObNm9m2bRu5ubn885//9HQsEQCOHDnCpEmTKCkp8XSUm55KQwDnG0YGBQU5bhgp4g3y8vLIyspqdpcIcT+vuk5DPMfIDSNFPGXx4sWejiD/pi0NAYzdMFJERKUhwOWbwH37edot3TBSRESlIYBuGCkixuiYhgC6YaSIGKPbiIiIiGHaPSUiIoapNERExDCVhoiIGKbSEBERw1QaIiJimEpDbkgfffQR8fHxrbKs/Px8Zs6c2Wx8165dPPfcc62yju/69a9/zSeffNJqy7vjjju4cOFCqy1Pbl66TkPkOo0aNYpRo0Z5OoaIW6kcwYFKAAAEMUlEQVQ05IZ18eJF5s6dy+nTpwkJCWHRokV07tyZ//mf/+Gzzz7DZDJx77338vvf/x4/Pz8OHTrE8uXLuXTpEm3atOHxxx9vdlV8YWEhK1as4NVXX+Uf//gH7777LmvXriU5OZkBAwbw97//nbNnzxITE8Ozzz6Lj48P+fn5vPrqqwQGBjJ06FDeeOMNPv300x/Mv3nzZj777DPq6+t55JFHmDBhAgC5ubls3LgRHx8fOnfuzDPPPENUVBTV1dXf+9lEWot+m+SGdfbsWVasWEF0dDS5ubmkp6fTs2dPOnTowI4dO7DZbMyaNYs//vGPPPTQQ8ydO5eXX36Z/v37c/LkSaZMmcKWLVscy9u5cyevvPIKGzdupGvXrvzjH/9wWt+ZM2fYuHEjFy9eZMyYMRw4cIDOnTuzYsUK8vPzCQ8PJzs7m8bGRkP5AwIC2Lp1KxaLhYSEBPr378/58+d57bXXyM3NpWPHjuTn5zNnzhz+/Oc/89xzz7X42WbMmNGqP1e5uemYhtyw7rjjDqKjowFISEiguLiY3bt3M2XKFEwmE/7+/iQmJvLBBx9w9OhRfv7zn9O/f38AevfuTXR0NAcOHADgk08+IT09ncTERLp27dri+kaOHImPjw/t27cnMjKSf/3rX+zbt4+7776b8PBwAKZMmWI4f2JiInD5Fi933303+/fv529/+xv3338/HTt2BGD8+PFYLBbKysr44IMPWvxsIq1JpSE3LB8f519vk8nk+LqiqamJhoYGGhsbm90K3m6309DQAEBwcDDr169n9erV3/u40cDAQKd12e12fH19+fadenx9fa8rf1NTE35+fjQ1NTWb70rO797e/spnE2lNKg25YZ04cYLjx48Dl48DDBo0iHvvvZdNmzZht9upr68nLy+PYcOGMWDAAL788kvHg6dOnjzJwYMHueuuuwDo0aMHMTExJCcn89RTT7X4z7sl99xzD/v378disQDw5ptvGs6/detWACoqKti/fz8xMTHce++9vP32244zod566y06dOhAZGQk99xzT4ufTaQ16ZiG3LB69uxJdnY2paWldOrUiWXLlhEUFMRzzz2H2WzGZrNx77338rvf/Q5/f3/+7//+j2effZba2lpMJhNLly4lKiqKjz/+2LHM3/3ud+zevZvXXnuNzp07/2CGqKgo5s+fz29/+1v8/f3p27cvbdu2NZS/rq6OhIQEbDYbmZmZREVFERUVxdSpU0lNTaWpqYmOHTuydu1afHx8yMzMbPGzibQm3eVWxIVKS0vZvn07s2fPxsfHh/fee49169Zd0xaHiDfRloaIC4WHh3Pu3DnMZjO+vr4EBwezZMkSCgoKWL9+fYvvMZvNTJ8+3c1JRYzRloaIiBimA+EiImKYSkNERAxTaYiIiGEqDRERMUylISIihqk0RETEsP8PIl+rBabcEcoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aab744ed68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.boxplot(x=\"booking_bool\", y=\"price_usd\", hue=\"booking_bool\", data=us)\n",
    "ax.set_ylim([0, 200]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>booking_bool</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3369149.0</td>\n",
       "      <td>159.795939</td>\n",
       "      <td>1434.330155</td>\n",
       "      <td>0.04</td>\n",
       "      <td>82.0</td>\n",
       "      <td>119.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>505455.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>98134.0</td>\n",
       "      <td>135.533224</td>\n",
       "      <td>927.366517</td>\n",
       "      <td>0.06</td>\n",
       "      <td>79.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>172761.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  count        mean          std   min   25%    50%    75%  \\\n",
       "booking_bool                                                                 \n",
       "0             3369149.0  159.795939  1434.330155  0.04  82.0  119.0  178.0   \n",
       "1               98134.0  135.533224   927.366517  0.06  79.0  109.0  152.0   \n",
       "\n",
       "                   max  \n",
       "booking_bool            \n",
       "0             505455.0  \n",
       "1             172761.0  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us.groupby('booking_bool')['price_usd'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On average, the price_usd that received a click or booking is always lower than those of did not get a click or booking."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aab9b18f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "correlation = us.corr()\n",
    "plt.figure(figsize=(18, 18))\n",
    "sns.heatmap(correlation, vmax=1, square=True,annot=True,cmap='viridis')\n",
    "plt.title('Correlation between different fearures');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Balance  the data\n",
    "\n",
    "For fast learning, our balancing strategy is down sampling negative instances."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Percentage of not click impressions:  0.5\n",
      "Percentage of click impression:  0.5\n",
      "Total number of records in resampled data:  300560\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "click_indices = us[us.click_bool == 1].index\n",
    "random_indices = np.random.choice(click_indices, len(us.loc[us.click_bool == 1]), replace=False)\n",
    "click_sample = us.loc[random_indices]\n",
    "\n",
    "not_click = us[us.click_bool == 0].index\n",
    "random_indices = np.random.choice(not_click, sum(us['click_bool']), replace=False)\n",
    "not_click_sample = us.loc[random_indices]\n",
    "\n",
    "us_new = pd.concat([not_click_sample, click_sample], axis=0)\n",
    "\n",
    "print(\"Percentage of not click impressions: \", len(us_new[us_new.click_bool == 0])/len(us_new))\n",
    "print(\"Percentage of click impression: \", len(us_new[us_new.click_bool == 1])/len(us_new))\n",
    "print(\"Total number of records in resampled data: \", len(us_new))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.ensemble import GradientBoostingClassifier\n",
    "from sklearn.ensemble import BaggingClassifier\n",
    "from sklearn.ensemble import AdaBoostClassifier\n",
    "from sklearn.ensemble import ExtraTreesClassifier\n",
    "from sklearn.neural_network import MLPClassifier\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.naive_bayes import BernoulliNB\n",
    "from sklearn.naive_bayes import MultinomialNB\n",
    "from sklearn import metrics\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import MinMaxScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "mms = MinMaxScaler()\n",
    "us_new[['price_usd','orig_destination_distance']] = mms.fit_transform(us_new[['price_usd','orig_destination_distance']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SusanLi\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\ipykernel_launcher.py:2: FutureWarning: reshape is deprecated and will raise in a subsequent release. Please use .values.reshape(...) instead\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "# MinMax=MinMaxScaler()\n",
    "# df['price_usd']=MinMax.fit_transform(df['price_usd'].values.reshape(-1,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "Y1=us_new['click_bool'].as_matrix()\n",
    "Y2=us_new['booking_bool'].as_matrix()\n",
    "us_new=us_new.drop(['click_bool','booking_bool'], 1)\n",
    "X=us_new.as_matrix()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.isnan(np.sum(X))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train,X_test,y_train,y_test = train_test_split(X,Y1,test_size=0.3,random_state=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rf =RandomForestClassifier(n_estimators=51,min_samples_leaf=5,min_samples_split=3)\n",
    "    bagg = BaggingClassifier(n_estimators=71,random_state=42)\n",
    "    extra = ExtraTreesClassifier(n_estimators=57,random_state=42)\n",
    "    ada = AdaBoostClassifier(n_estimators=51,random_state=42)\n",
    "    grad = GradientBoostingClassifier(n_estimators=101,random_state=42)\n",
    "    classifier_list = [rf,bagg,extra,ada,grad]\n",
    "    classifier_name_list = ['Random Forests','Bagging','Extra Trees','AdaBoost','Gradient Boost']\n",
    "    return classifier_list,classifier_name_list"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Click-through prediction with ensemble models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_ensemble_models():\n",
    "    rf =RandomForestClassifier(n_estimators=51,min_samples_leaf=5,min_samples_split=3)\n",
    "    bagg = BaggingClassifier(n_estimators=51,random_state=42)\n",
    "    extra = ExtraTreesClassifier(n_estimators=51,random_state=42)\n",
    "    ada = AdaBoostClassifier(n_estimators=51,random_state=42)\n",
    "    grad = GradientBoostingClassifier(n_estimators=51,random_state=42)\n",
    "    classifier_list = [rf,bagg,extra,ada,grad]\n",
    "    classifier_name_list = ['Random Forests','Bagging','Extra Trees','AdaBoost','Gradient Boost']\n",
    "    return classifier_list,classifier_name_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "def print_evaluation_metrics(trained_model,trained_model_name,X_test,y_test):\n",
    "    print('--------- Model : ', trained_model_name, ' ---------------\\n')\n",
    "    predicted_values = trained_model.predict(X_test)\n",
    "    print(metrics.classification_report(y_test,predicted_values))\n",
    "    print(\"Accuracy Score : \",metrics.accuracy_score(y_test,predicted_values))\n",
    "    print(\"---------------------------------------\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------- Model :  Random Forests  ---------------\n",
      "\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          0       0.70      0.70      0.70     45275\n",
      "          1       0.70      0.70      0.70     44893\n",
      "\n",
      "avg / total       0.70      0.70      0.70     90168\n",
      "\n",
      "Accuracy Score :  0.702821400053234\n",
      "---------------------------------------\n",
      "\n",
      "--------- Model :  Bagging  ---------------\n",
      "\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          0       0.69      0.69      0.69     45275\n",
      "          1       0.69      0.69      0.69     44893\n",
      "\n",
      "avg / total       0.69      0.69      0.69     90168\n",
      "\n",
      "Accuracy Score :  0.690732854227664\n",
      "---------------------------------------\n",
      "\n",
      "--------- Model :  Extra Trees  ---------------\n",
      "\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          0       0.69      0.69      0.69     45275\n",
      "          1       0.69      0.69      0.69     44893\n",
      "\n",
      "avg / total       0.69      0.69      0.69     90168\n",
      "\n",
      "Accuracy Score :  0.689368733918907\n",
      "---------------------------------------\n",
      "\n",
      "--------- Model :  AdaBoost  ---------------\n",
      "\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          0       0.69      0.72      0.71     45275\n",
      "          1       0.71      0.68      0.69     44893\n",
      "\n",
      "avg / total       0.70      0.70      0.70     90168\n",
      "\n",
      "Accuracy Score :  0.6983519652204774\n",
      "---------------------------------------\n",
      "\n",
      "--------- Model :  Gradient Boost  ---------------\n",
      "\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          0       0.69      0.72      0.70     45275\n",
      "          1       0.70      0.68      0.69     44893\n",
      "\n",
      "avg / total       0.70      0.70      0.70     90168\n",
      "\n",
      "Accuracy Score :  0.6988510336261201\n",
      "---------------------------------------\n",
      "\n"
     ]
    }
   ],
   "source": [
    "classifier_list, classifier_name_list = get_ensemble_models()\n",
    "for classifier,classifier_name in zip(classifier_list,classifier_name_list):\n",
    "    classifier.fit(X_train,y_train)\n",
    "    print_evaluation_metrics(classifier,classifier_name,X_test,y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Click-through prediction with Naive bayes models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_naive_bayes_models():\n",
    "    gnb = GaussianNB()\n",
    "    mnb = MultinomialNB()\n",
    "    bnb = BernoulliNB()\n",
    "    classifier_list = [gnb,mnb,bnb]\n",
    "    classifier_name_list = ['Gaussian NB','Multinomial NB','Bernoulli NB']\n",
    "    return classifier_list,classifier_name_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------- Model :  Gaussian NB  ---------------\n",
      "\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          0       0.70      0.61      0.65     45275\n",
      "          1       0.65      0.74      0.69     44893\n",
      "\n",
      "avg / total       0.68      0.67      0.67     90168\n",
      "\n",
      "Accuracy Score :  0.6745297666577943\n",
      "---------------------------------------\n",
      "\n",
      "--------- Model :  Multinomial NB  ---------------\n",
      "\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          0       0.66      0.63      0.65     45275\n",
      "          1       0.64      0.68      0.66     44893\n",
      "\n",
      "avg / total       0.65      0.65      0.65     90168\n",
      "\n",
      "Accuracy Score :  0.6530698252151539\n",
      "---------------------------------------\n",
      "\n",
      "--------- Model :  Bernoulli NB  ---------------\n",
      "\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          0       0.53      0.77      0.63     45275\n",
      "          1       0.57      0.31      0.41     44893\n",
      "\n",
      "avg / total       0.55      0.54      0.52     90168\n",
      "\n",
      "Accuracy Score :  0.5425871706148523\n",
      "---------------------------------------\n",
      "\n"
     ]
    }
   ],
   "source": [
    "classifier_list, classifier_name_list = get_naive_bayes_models()\n",
    "for classifier,classifier_name in zip(classifier_list,classifier_name_list):\n",
    "    classifier.fit(X_train,y_train)\n",
    "    print_evaluation_metrics(classifier,classifier_name,X_test,y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Click-through prediction with Neural network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_neural_network(hidden_layer_size=50):\n",
    "    mlp = MLPClassifier(hidden_layer_sizes=hidden_layer_size)\n",
    "    return [mlp], ['MultiLayer Perceptron']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------- Model :  MultiLayer Perceptron  ---------------\n",
      "\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          0       0.51      0.99      0.67     45275\n",
      "          1       0.72      0.02      0.04     44893\n",
      "\n",
      "avg / total       0.61      0.51      0.36     90168\n",
      "\n",
      "Accuracy Score :  0.5086616094401561\n",
      "---------------------------------------\n",
      "\n"
     ]
    }
   ],
   "source": [
    "classifier_list, classifier_name_list = get_neural_network()\n",
    "for classifier,classifier_name in zip(classifier_list,classifier_name_list):\n",
    "    classifier.fit(X_train,y_train)\n",
    "    print_evaluation_metrics(classifier,classifier_name,X_test,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x27c3c5dec88>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x27c3c374c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rf = RandomForestClassifier(n_estimators=51,min_samples_leaf=5,min_samples_split=3)\n",
    "rf.fit(X_train, y_train)\n",
    "(pd.Series(rf.feature_importances_, index=us_new.columns).plot(kind='barh'))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
